Interactive Fibre Structure Visualization of the Heart

The heart consists of densely packed muscle fibres. The orientation of these fibres can be acquired by using Diffusion Tensor Imaging (DTI) ex vivo. A good way to visualize the fibre structure in a cross section of the heart is by showing short line segments originating from the cross section and aligned with the local direction of the fibres. If the line segments are placed dense enough, one can see how the fibre orientations change. However, generation of the line segments takes time and thus the user has to wait for new geometry to be generated when the plane defining the cross section is changed. We present a new direct rendering method for the visualization of the 3D vector field in a 2D user‐definable cross section of a heart. On the intersection of the plane with the vector field, the full 3D vectors are rendered as 3D line segments with a local ray casting approach. No preprocessing of the data is needed and no geometry is generated. This technique allows a fast inspection of the data to identify interesting areas where further analysis is necessary (e.g. quantification or generation of streamlines). We also show how the technique is generalized to other glyph shapes than line segments by implementing ellipsoids.     

Robust Cardiac Function Assessment in 4D PC‐MRI Data of the Aorta and Pulmonary Artery

Four‐dimensional phase‐contrast magnetic resonance imaging (4D PC‐MRI) allows the non‐invasive acquisition of time‐resolved, 3D blood flow information. Stroke volumes (SVs) and regurgitation fractions (RFs) are two of the main measures to assess the cardiac function and severity of valvular pathologies. The flow rates in forward and backward direction through a plane above the aortic or pulmonary valve are required for their quantification. Unfortunately, the calculations are highly sensitive towards the plane's angulation since orthogonally passing flow is considered. This often leads to physiologically implausible results. In this work, a robust quantification method is introduced to overcome this problem. Collaborating radiologists and cardiologists were carefully observed while estimating SVs and RFs in various healthy volunteer and patient 4D PC‐MRI data sets with conventional quantification methods, that is, using a single plane above the valve that is freely movable along the centerline. By default it is aligned perpendicular to the vessel's centerline, but free angulation (rotation) is possible. This facilitated the automation of their approach which, in turn, allows to derive statistical information about the plane angulation sensitivity. Moreover, the experts expect a continuous decrease of the blood flow volume along the vessel course. Conventional methods are often unable to produce this behaviour. Thus, we present a procedure to fit a monotonous function that ensures such physiologically plausible results. In addition, this technique was adapted for the usage in branching vessels such as the pulmonary artery. The performed informal evaluation shows the capability of our method to support diagnosis; a parameter evaluation confirms the robustness. Vortex flow was identified as one of the main causes for quantification uncertainties.     

Visual Analysis of Tumor Control Models for Prediction of Radiotherapy Response

In radiotherapy, tumors are irradiated with a high dose, while surrounding healthy tissues are spared. To quantify the probability that a tumor is effectively treated with a given dose, statistical models were built and employed in clinical research. These are called tumor control probability (TCP) models. Recently, TCP models started incorporating additional information from imaging modalities. In this way, patient‐specific properties of tumor tissues are included, improving the radiobiological accuracy of models. Yet, the employed imaging modalities are subject to uncertainties with significant impact on the modeling outcome, while the models are sensitive to a number of parameter assumptions. Currently, uncertainty and parameter sensitivity are not incorporated in the analysis, due to time and resource constraints. To this end, we propose a visual tool that enables clinical researchers working on TCP modeling, to explore the information provided by their models, to discover new knowledge and to confirm or generate hypotheses within their data. Our approach incorporates the following four main components: (1) It supports the exploration of uncertainty and its effect on TCP models; (2) It facilitates parameter sensitivity analysis to common assumptions; (3) It enables the identification of inter‐patient response variability; (4) It allows starting the analysis from the desired treatment outcome, to identify treatment strategies that achieve it. We conducted an evaluation with nine clinical researchers. All participants agreed that the proposed visual tool provides better understanding and new opportunities for the exploration and analysis of TCP modeling.     

Exploring Collections of Tagged Text for Literary Scholarship

Modern literary scholars must combine access to vast collections of text with the traditional close analysis of their field. In this paper, we discuss the design and development of tools to support this work. Based on analysis of the needs of literary scholars, we constructed a suite of visualization tools for the analysis of large collections of tagged text (i.e. text where one or more words have been annotated as belonging to a specific category). These tools unite the aspects of the scholars’ work: large scale overview tools help to identify corpus‐wide statistical patterns while fine scale analysis tools assist in finding specific details that support these observations. We designed visual tools that support and integrate these levels of analysis. The result is the first tool suite that can support the multilevel text analysis performed by scholars, combining standard visual elements with novel methods for selecting individual texts and identifying represenative passages in them.     

Topology‐based Visualization of Transformation Pathways in Complex Chemical Systems

Studying transformation in a chemical system by considering its energy as a function of coordinates of the system's components provides insight and changes our understanding of this process. Currently, a lack of effective visualization techniques for high‐dimensional energy functions limits chemists to plot energy with respect to one or two coordinates at a time. In some complex systems, developing a comprehensive understanding requires new visualization techniques that show relationships between all coordinates at the same time. We propose a new visualization technique that combines concepts from topological analysis, multi‐dimensional scaling, and graph layout to enable the analysis of energy functions for a wide range of molecular structures. We demonstrate our technique by studying the energy function of a dimer of formic and acetic acids and a LTA zeolite structure, in which we consider diffusion of methane.     

A Graph‐based Approach to Continuous Line Illustrations with Variable Levels of Detail

This paper introduces a method for automatically generating continuous line illustrations, drawings consisting of a single line, from a given input image. Our approach begins by inferring a graph from a set of edges extracted from the image in question and obtaining a path that traverses through all edges of the said graph. The resulting path is then subjected to a series of post‐processing operations to transform it into a continuous line drawing. Moreover, our approach allows us to manipulate the amount of detail portrayed in our line illustrations, which is particularly useful for simplifying the overall illustration while still retaining its most significant features. We also present several experimental results to demonstrate that our approach can automatically synthesize continuous line illustrations comparable to those of some contemporary artists.     

在ASP中运用Crystal Reports实现报表打印

结合开发与应用实践,介绍了在ASP平台下调用Crystal Reports报表设计软件实现数据打印的原理和方法。     

Feature Extraction using Unit-linking Pulse Coupled Neural Network and its Applications

In this paper, we use Unit-linking PCNN (Pulse Coupled Neural Network), the simplified model of PCNN consisting of spiking neurons, to code a 2-dimensional image into a 1-dimensional time sequence called global Unit-linking PCNN image icon or time signature, including features of the original image and having the translation, rotation, and scale invariance. Dividing an image into multiple parts can obtain local Unit-linking PCNN image icons corresponding to the image’s local regions, which can reflect the local changes of the image. In the meantime, the global and the local Unit-linking PCNN image icons are used in navigation, object detection, and image authentication. In navigation, global Unit-linking PCNN image icon shows qualified performance especially in non-stationary-video navigation. Object detection using global Unit-linking PCNN image icon, is independent of variances of translation, rotation, and scale, and object segmentation is avoided. In image authentication, using local Unit-linking PCNN image icon can authenticate correctly some juggled images failed to authenticate by using local histogram or local mean intensity, and can locate the juggled positions in the juggled images with some accuracy.     

分层分类教学法在“计算机应用基础”课程中的应用

本文分析了目前计算机应用基础教学中存在的若干问题,并结合地方性高校的实际情况,针对各个问题分别提出了可行的对策,最后说明了实施的情况和取得的教学效果。     

聚酰胺工程塑料的发展

介绍国内外聚酰胺工程塑料的发展历史和现状,各种聚酰胺新品种和新成型工艺技术的研究与开发动向,并对我国发展聚酰胺工程塑料提出了建议。